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The Active Elastic Model

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Information Processing in Medical Imaging (IPMI 2001)

Abstract

Continuum mechanical models have been used to regularize ill-posed problems in many applications in medical imaging analysis such as image registration and left ventricular motion estimation. In this work, we present a significant extension to the common elastic model which we call the active elastic model. The active elastic model is designed to reduce bias in deformation estimation and to allow the imposition of proper priors on deformation estimation problems that contain information regarding both the expected magnitude and the expected variability of the deformation to be estimated. We test this model on the problem of left ventricular deformation estimation, and present ideas for its application in image registration and brain deformation during neurosurgery.

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References

  1. F. L. Bookstein. Principal warps: Thin-plate splines and the decomposition of deformations. IEEE Transactions on Pattern Analysis and Machine Intelligence, pages 567–585, 1989.

    Google Scholar 

  2. G. E. Christensen. Deformable Shape Models for Anatomy. Ph. D. dissertation, Washington University, Saint Louis, MI, August 1994.

    Google Scholar 

  3. G. E. Christensen, R. D. Rabbitt, and M. I. Miller M. I. Deformable templates using large deformation kinematics. IEEE Transactions on Image Processing, 5(10):1435–1447, 1996.

    Article  Google Scholar 

  4. H. Chui, J. Rambo, R. Schultz, L. Win, J. Duncan, and A. Rangarajan. Registration of cortical anatomical structures via 3d robust point matching. In Information Processing in Medical Imaging, pages 168–181, Visegrad, Hungary, June 1999.

    Google Scholar 

  5. L. D. Cohen and I. Cohen. Finite element methods for active contour models and balloons for 2D and 3D images. IEEE Trans. Pattern Analysis and Machine Intelligence, 15(11):1131–1147, November 1993.

    Article  Google Scholar 

  6. T. Cootes, A. Hill, C. Taylor, and J. Haslam. The use of active shape models for locating structures in medical images. In H. H. Barrett and A. F. Gmitro, editors, Information Processing in Medical Imaging, pages 33–47. LNCS 687, Springer-Verlag, Berlin, 1993.

    Chapter  Google Scholar 

  7. T. F. Cootes, C. J. Taylor, D. H. Cooper, and J. Graham. Active shape models-their training and application. Comp. Vision and Image Understanding, 61(1):38–59, 1995.

    Article  Google Scholar 

  8. A. C. Eringen. Mechanics of Continua. Krieger, New York, NY, 1980.

    Google Scholar 

  9. J. C. Gee, D. R. Haynor, L. Le Briquer, and R. K. Bajcsy. Advances in elastic matching theory and its implementation. In CVRMed-MRCAS, Grenoble, France, March 1997.

    Google Scholar 

  10. D. Geman and S. Geman. Stochastic relaxation, Gibbs distribution and Bayesian restoration of images. IEEE Transactions on Pattern Analysis and Machine Intelligence, 6:721–741, 1984.

    Article  MATH  Google Scholar 

  11. E. Haber, D. N. Metaxas, and L. Axel. Motion analysis of the right ventricle from MRI images. In Medical Image Computing and Computer Aided Intervention (MICCAI), pages 177–188, Cambridge, MA, October 1998.

    Google Scholar 

  12. B. K. P. Horn and B. G. Schunk. Determining optical flow. Artificial Intelligence, 17:185–203, 1981.

    Article  Google Scholar 

  13. M. Kass, A. Witkin, and D. Terzopoulus. Snakes: Active contour models. International Journal of Computer Vision, 1:312–331, 1988.

    Google Scholar 

  14. W. S. Kerwin and J. L. Prince. Cardiac material markers from tagged MR images. Medical Image Analysis, 2(4):339–353, 1998.

    Article  Google Scholar 

  15. S. Kyriakou and C. Davatzikos. A biomechanical model of soft tissue deformation with applications to non-rigid registration of brain image with tumor pathology. In Medical Image Computing and Computer Assisted Intervention, pages 531–538. Springer, Berlin, 1998. LNCS 1496.

    Google Scholar 

  16. T. McInerney and D. Terzopoulos. Deformable models in medical image analysis: a survey. Medical Image Analysis, 1(2):91–108, 1996.

    Article  Google Scholar 

  17. X. Papademetris, A. J. Sinusas, D. P. Dione, and J. S. Duncan. Estimation 3D left ventricular deformation from echocardiography. Medical Image Analysis, in-press (March 2001).

    Google Scholar 

  18. X. Papademetris, A. J. Sinusas, D. P. Dione, and J. S. Duncan R. T. Constable. Estimating 3D strain from 4D cine-MRI and echocardiography: In-vivo validation. In Medical Image Computing and Computer Aided Intervention (MICCAI), Pittsburgh, U.S.A., October 2000.

    Google Scholar 

  19. J. Park, D. N. Metaxas, and L. Axel. Analysis of left ventricular wall motion based on volumetric deformable models and MRI-SPAMM. Medical Image Analysis, 1(1):53–71, 1996.

    Article  Google Scholar 

  20. P. Shi, A. J. Sinusas, R. T. Constable, E. Ritman, and J. S. Duncan. Point-tracked quantitative analysis of left ventricular motion from 3D image sequences. IEEE Transactions on Medical Imaging,, 19(1):36–50, January 2000.

    Article  Google Scholar 

  21. O. Skrinjar and J. Duncan. Real time 3D brain shift compensation. In Information Processing in Medical Imaging (IPMI 99), pages 42–55, 1999.

    Google Scholar 

  22. A. Spencer. Continuum Mechanics. Longman, London, 1980.

    Google Scholar 

  23. Y. Wang and L. H. Staib. Elastic model based non-rigid registration incorporating statistical shape information. In Medical Image Computing and Computer Aided Intervention (MICCAI), pages 1162–1173. Springer, Berlin, 1998. LNCS 1496.

    Google Scholar 

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© 2001 Springer-Verlag Berlin Heidelberg

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Papademetris, X., Constable, R.T., Onat, E.T., Duncan, J.S., Sinusas, A.J., Dione, D.P. (2001). The Active Elastic Model. In: Insana, M.F., Leahy, R.M. (eds) Information Processing in Medical Imaging. IPMI 2001. Lecture Notes in Computer Science, vol 2082. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45729-1_4

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  • DOI: https://doi.org/10.1007/3-540-45729-1_4

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42245-7

  • Online ISBN: 978-3-540-45729-9

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